# v2
dataset_train = build_dataset(is_train=True, args=args)
dataset_val = build_dataset(is_train=False, args=args)
dataset = datasets.ImageFolder(root, transform=transform)

sampler_train = torch.utils.data.RandomSampler(dataset_train)
sampler_val = torch.utils.data.SequentialSampler(dataset_val)

data_loader_train = torch.utils.data.DataLoader(
    dataset_train,
    sampler=sampler_train,
    batch_size=args.batch_size,
    num_workers=args.num_workers,
    pin_memory=args.pin_mem,
    drop_last=True,
    )

data_loader_val = torch.utils.data.DataLoader(
    dataset_val,
    sampler=sampler_val,
    batch_size=args.batch_size,
    num_workers=args.num_workers,
    pin_memory=args.pin_mem,
    drop_last=False,
    )
########################################################
# GAC
train_dataset, val_dataset = data_loaders.build_cifar(use_cifar10=False)# C,H,W
train_dataset = CIFAR10(root='./data',
                                train=True, download=download, transform=transform_train)

train_loader = torch.utils.data.DataLoader(train_dataset, batch_size=args.batch_size, shuffle=True,
                                               num_workers=args.workers, pin_memory=True)# B,C,H,W
test_loader = torch.utils.data.DataLoader(val_dataset, batch_size=args.batch_size,
                                              shuffle=False, num_workers=args.workers, pin_memory=True)# B,C,H,W
########################################################
# v1dvs



